{"title":"Hardware Support for Secure Stream Processing in Cloud Environments","authors":"Jeff Anderson, T. El-Ghazawi","doi":"10.1145/3075564.3075592","DOIUrl":null,"url":null,"abstract":"Many-core microprocessor architectures are quickly becoming prevalent in data centers, due to their demonstrated processing power and network flexibility. However, this flexibility comes at a cost; co-mingled data from disparate users must be kept secure, which forces processor cycles to be wasted on cryptographic operations. This paper introduces a novel, secure, stream processing architecture which supports efficient homomorphic authentication of data and enforces secrecy of individuals' data. Additionally, this architecture is shown to secure time-series analysis of data from multiple users from both corruption and disclosure. Hardware synthesis shows that security-related circuitry incurs less than 10% overhead, and latency analysis shows an increase of 2 clocks per hop. However, despite the increase in latency, the proposed architecture shows an improvement over stream processing systems that use traditional security methods.","PeriodicalId":398898,"journal":{"name":"Proceedings of the Computing Frontiers Conference","volume":"39 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the Computing Frontiers Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3075564.3075592","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
Many-core microprocessor architectures are quickly becoming prevalent in data centers, due to their demonstrated processing power and network flexibility. However, this flexibility comes at a cost; co-mingled data from disparate users must be kept secure, which forces processor cycles to be wasted on cryptographic operations. This paper introduces a novel, secure, stream processing architecture which supports efficient homomorphic authentication of data and enforces secrecy of individuals' data. Additionally, this architecture is shown to secure time-series analysis of data from multiple users from both corruption and disclosure. Hardware synthesis shows that security-related circuitry incurs less than 10% overhead, and latency analysis shows an increase of 2 clocks per hop. However, despite the increase in latency, the proposed architecture shows an improvement over stream processing systems that use traditional security methods.